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Record W4308773580 · doi:10.1097/spc.0000000000000621

Fertility preservation in uro-oncology

2022· review· en· W4308773580 on OpenAlexaff
Kieran Moore, Jesse Ory

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2022
Typereview
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineFertility preservationFertilityMEDLINEOncologyGynecologyInternal medicineIntensive care medicineEnvironmental health

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The purpose of this review is to highlight the demand for fertility preservation among cancer survivors and to draw attention to areas where healthcare workers need to improve. As technology advances, maximizing cryopreservation rates will be paramount to increase the ability individuals to conceive after cancer treatment. RECENT FINDINGS: Guidelines recommending discussion of fertility for those diagnosed with cancer have been shown to increase patient satisfaction and overall quality of life. Our review demonstrated that increasing counseling rates remains an ongoing challenge and should remain an area of improvement for all healthcare professionals working in the oncology field. Formal programs to improve patient and provider education and access to fertility preservation increase uptake of fertility preservation. For men, many options exist to cryopreserve sperm; a slight delay to achieve fertility preservation has not been shown to lead to worse outcomes. Cryopreservation strategies differ based on puberty status and remain an active area of clinical research. SUMMARY: Improving fertility outcomes for cancer survivors is possible with appropriate counseling techniques at the time of cancer diagnosis. Clinicians should challenge current barriers for patient access to fertility preservation surrounding cancer treatments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.315
GPT teacher head0.491
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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